教育・健康１

16:50 〜 17:05

[kNAyHR2S-01] Development of an AI-Enhanced Decision Support System for Female Patients with Stress Urinary Incontinence

*Haoran Zhu¹, Liwei Jing¹ (1. Capital Medical University (China))

キーワード：

Older Women、Stress Urinary Incontinence、Severity Assessment、Decision Support System

Purpose: Stress urinary incontinence (SUI) is common among middle-aged and older women, significantly affecting their quality of life. However, current severity assessments are often subjective and inefficient, and patients also lack adequate support when facing treatment decisions. This study aims to develop an AI-driven decision support system (DSS) that enables accurate SUI severity assessment and provides personalized decision guidance for older women. Methods: The assessment indicator system was built upon patients' chief complaints, ICIQ-SF scores, and pelvic muscle physiological signals. An ensemble learning strategy was applied to construct an innovative unconstrained probabilistic embedding framework, centered on support vector regression (SVR) and integrating multiple models for precise severity quantification. A decision guidance module was also developed based on the Ottawa Decision Support Framework (ODSF), structuring decision-related information in a cognitively accessible manner. Result: The study constructed a decision support system for middle-aged and older women with urinary incontinence. The dual-module system consists of a severity assessment engine and a personalized decision guidance interface, classifying severity levels and generate individualized decision suggestions aligned with older patients' needs, preferences, and comprehension levels. Consideration: This study focuses on the conceptual design and technical realization of the system. In future stages, real-world testing and optimization will be needed to further improve usability and clinical applicability. The current design prioritizes interpretability and simplicity for aging users. Conclusion: This study successfully developed an AI-based decision support system tailored for middle-aged and older women with SUI. By integrating objective severity assessment with structured decision guidance, the system provides a novel tool to support early identification, informed choice, and proactive participation in managing urinary health.